Feasibility of detecting changes in diary-based seizure cycles following antiseizure medication changes: A...

Evaluating effectiveness of antiseizure medications (ASMs) in epilepsy relies on diary reported seizure frequency, before and after treatment initiation. Measuring efficacy with seizure frequency can be challenging as seizures can occur in cyclical patterns (i.e. seizure cycles), making it difficult to distinguish drug effects from natural fluctuations. Incorporating cycle information could aid treatment evaluation, but cycles are non-stationary and possibly altered by ASMs. Whether changes in cycles following ASM changes can be detected in noisy diary data remains unclear.

We conducted a pilot study evaluating the feasibility of using mobile app-based seizure and medication adherence diaries in 86 individuals with epilepsy, to detect changes in seizure timing around ASM regime modifications. We explored diary-derived seizure cycle metrics across two groups: individuals undergoing ASM regimen changes and individuals with no ASM modifications. Groups were compared on changes in three cycle metrics: 1. how strongly seizures synchronise with a cycle, measured by the corrected Synchronisation Index (SI), 2. cycle period, and 3. number of detected cycles. Permutation tests assessed significance, and linear regression examined seizure rate correlations.

Compared with the drug-sustained group, the drug-switching group demonstrated larger pre-post changes in SI, with the strongest effect in drug-switching-responders (median absolute SI difference of the new dominant cycle: 0.37 [IQR=0.26] vs. 0.11 [IQR=0.11] in drug-sustained-responders, p < 0.002, permutation test). Groups showed similar changes in cycle period and the number of detected cycles.

Despite inherent limitations, seizure diaries may be used to detect changes in seizure timing during ASM regimen changes, reinforcing their value for seizure cycle studies. Substantial challenges remain for clinical application.